THE COST OF GENDER INEQUALITY UNREALIZED POTENTIAL: THE HIGH COST OF GENDER INEQUALITY IN EARNINGS QUENTIN WODON AND BENEDICTE DE LA BRIERE MAY 2018 THE COST OF GENDER INEQUALITY UNREALIZED POTENTIAL: THE HIGH COST OF GENDER INEQUALITY IN EARNINGS QUENTIN WODON AND BENEDICTE DE LA BRIERE BACKGROUND TO THIS SERIES Reducing gender inequality makes economic sense In addition, many girls are married or have children apart from being the right thing to do. Achieving before the age of 18, before they may be physically gender equality and empowering all women and girls and emotionally ready to become wives and mothers. is the fifth sustainable development goal and is a top Women and girls also face higher risks of gender- priority for governments. Countries can achieve this based violence in their homes, at work, and in public goal if they take appropriate steps. This note is part spaces. Their voice and agency is often lower than of a series that aims to measure the economic cost of that of males, whether this is within the household, at gender inequality globally and regionally by examining work, or in national institutions. This also affects their the impacts of gender inequality in a wide range of areas children. For example, children of young and poorly and the costs associated with those impacts. Given educated mothers often face higher risks of dying by that gender inequality affects individuals throughout age five, being malnourished, and doing poorly in school. their life, economic costs are measured in terms of Fundamentally, gender inequality disempowers women losses in human capital wealth, as opposed to annual and girls in ways that deprive them of their basic human losses in income or economic growth. The notes also rights. aim to provide a synthesis of the available evidence on successful programs and policies that contribute This lack of opportunities for girls and women entails to gender equality in multiple areas and achieve the large economic costs not only for them, but also for Sustainable Development Goals (SDGs). their households and countries. Achieving gender equality would have dramatic benefits for women and In many countries, girls’ average educational attainment girls’ welfare and agency. This, in turn, would greatly remains lower than boys and adult women are less benefit their households and communities, and help literate than men. Apart from these gender gaps in countries reach their full development potential. It would educational attainment, discrimination and social norms reduce fertility in countries with high population growth, shape the terms of female labor force participation. as well as reduce under-five mortality and stunting, Women are less likely than men to join the labor force thereby contributing to ushering the demographic and to work for pay. When they do, they are more transition and the associated benefits from the likely to work part-time, in the informal sector, or in demographic dividend. occupations that have lower pay. These disadvantages translate into substantial gender gaps in earnings, which in turn decrease women’s bargaining power and voice. 1 | THE COST OF GENDER INEQUALITY: UNREALIZED POTENTIAL: THE HIGH COST OF GENDER INEQUALITY IN EARNINGS | MAY 2018 KEY RESULTS • These estimates of the losses from gender inequality are related only to differences in lifetime labor This first note in the series on the cost of gender inequality earnings and therefore human capital wealth focuses on the losses in national wealth due to gender between women and men. Many other costs are inequality in earnings. There is a substantial literature on associated with gender equality apart from those the impact of gender inequality on economic growth and estimated in this particular note. Subsequent notes performance. By focusing on wealth, the approach used in this series will estimate those other losses. for measurement in this note is different. Wealth is the assets base that enables countries to produce income • Two main factors lead women to have less earnings and (Gross Domestic Product or GDP). A country’s wealth thereby lower human capital wealth than men: lower includes various types of capital. Produced capital comes labor force participation rates and fewer hours worked from investments in assets such as factories, equipment, in the labor market, and lower pay. These factors keep or infrastructure. Natural capital includes assets such as many women in a productivity trap due in part to social agricultural land and other renewable and non-renewable norms relegating them to unpaid care and informal work. natural resources. However, the largest component of countries’ wealth typically resides in their people. As noted • To increase women’s earnings and human capital in the recent World Bank study on the Changing Wealth wealth, investments throughout the life cycle are of Nations (Lange et al., 2018), human capital measured needed, from early childhood development and as the present value of the future earnings of the labor learning in schools to building job-relevant skills that force accounts for two thirds of global wealth. If gender employers demand, encouraging entrepreneurship and equality in earnings were achieved, countries could increase innovation, and ensuring that both women and men their human capital wealth, and thereby their total wealth have equal access to opportunities and resources. substantially. This would enable them to strengthen the sustainability of their development path. Specifically, key • A review of the literature suggests that successful findings from this note are as follows: interventions can be implemented in multiple areas to improve employment opportunities and earnings • Globally, women account for only 38 percent of for women. This includes: (i) reducing time spent human capital wealth versus 62 percent for men. in unpaid work (notably subsistence and household In low- and lower-middle income countries, women work) and redistributing care responsibilities; (ii) account for a third or less of human capital wealth. increasing access to and control over productive assets (particularly land, credit, insurance and savings but also • On a per capita basis, gender inequality in earnings key skills); and (iii) addressing market and institutional could lead to losses in wealth of $23,620 per person failures (access to information and networks, legal and globally. These losses differ between regions and fiscal impediments, and restrictive social norms). countries because levels of human capital wealth, and thereby losses in wealth due to gender inequality, • Ending gender inequality by investing in girls and women tend to increase in absolute values with economic is essential to increase the changing wealth of nations development. For these reasons, in absolute terms and enable countries to develop in sustainable ways. This the losses are largest in OECD countries. makes economic sense and it is the right thing to do. • Globally, for the 141 countries included in the analysis, the loss in human capital wealth due to gender inequality is estimated at $160.2 trillion if we simply assume that women would earn as much as men. This is about twice the value of GDP globally. Said differently, human capital wealth could increase by 21.7 percent globally, and total wealth by 14.0 percent with gender equality in earnings. MAY 2018 | THE COST OF GENDER INEQUALITY: UNREALIZED POTENTIAL: THE HIGH COST OF GENDER INEQUALITY IN EARNINGS | 2 INTRODUCTION: WEALTH measuring lifetime losses in earnings. More precisely, human capital wealth is defined as the present value of AND THE COST OF the future earnings of today’s labor force, considering individuals aged 15 and above. GENDER INEQUALITY At least three arguments justify using a wealth (stock) Gender inequality has major economic implications for approach as opposed to a GDP (flow) approach to measure women, communities, and countries in a range of areas (see losses in earnings due to gender inequality. First, using the framework used for this series of notes in Appendix 1). a flow approach does not reveal the full magnitude of While the cost of gender inequality – in terms of human the losses in earnings faced by women throughout their capital losses - for development is not solely due to losses working life. Estimates of losses from gender inequality in earnings, the impact of gender inequality on earnings is in labor markets based on human capital wealth are key. This is the area on which this note focuses. Typically, substantially larger than those based on GDP simply researchers looking at the impact of gender inequality on because wealth is larger than GDP. The full magnitude development have focused on annual measures of income of the losses from gender inequality appears only when or growth in income (e.g. Elborgh-Woytek et al., 2013; considering human capital wealth or women’s earnings over Cuberes and Teigner, 2015; McKinsey Global Institute, their lifetime. 2015). These analyses focus on the potential losses in Gross Domestic Product (GDP) from inequality between women Second, a flow approach tends to emphasize losses for and men in labor markets. This focus on income is natural individuals at the peak of their earnings, since they account since GDP is the standard measure according to which the for a larger share of the labor earnings in GDP. Again, it economic performance of countries is measured today. seems more appropriate to look at individuals’ lifetime Yet GDP growth is a short-term measure of performance, earnings to better reflect expected losses from gender which may be misleading about the health of an economy inequality. This should give a higher weight to younger because it does not reflect whether a country is investing individuals than is the case with the flow approach. in the assets base that will sustain its long-term growth. For example, a country could deplete its natural capital base Third, and perhaps most fundamentally, a wealth approach or fail to invest in its people and still be able generate high is forward-looking as it emphasizes sustainability. As rates of GDP growth in the short run, although probably already mentioned, countries’ economic development not in the long-run. has traditionally been assessed through GDP per capita, a measure of the income produced by a nation in a In this note, we rely on a different approach to measure given year. Similarly, economic performance has been the losses in earnings that result from gender inequality or, traditionally assessed through growth in GDP per capita. equivalently, the gains associated with gender equality in This is perhaps why most studies of the impact of gender labor markets. Instead of measuring losses from inequality inequality on earnings have focused on GDP. But with as annual flows (the GDP approach), we focus on losses which resources is GDP produced? GDP, or more precisely in human capital (the wealth approach). This is done by the consumption component of GDP, is essentially is 3 | THE COST OF GENDER INEQUALITY: UNREALIZED POTENTIAL: THE HIGH COST OF GENDER INEQUALITY IN EARNINGS | MAY 2018 the annual return or income that a country reaps from As mentioned earlier, total wealth includes natural capital, its wealth, the assets base that it uses for production. produced capital, human capital, and net foreign assets. Wealth consists of natural capital such as agricultural land, forest, oil, gas and minerals, to give a few examples. It also Global wealth stood at $1,143 trillion in 2014. This consists of produced capital – think about infrastructure, represented an increase in real terms of 66 percent over 20 machinery, factories, or buildings. Finally, wealth consists years (average annual growth rate of 2.6 percent per year). of human capital, such as a well-educated and productive Human capital wealth reached $737 trillion in 2014, an labor force. These three categories – produced, natural, and increase of 55 percent since 1995 (average annual growth human capital, are considered the three main components rate of 2.2 percent). Globally, human capital accounts for of the changing wealth of nations, that together with net more than two thirds of total wealth, versus just under one foreign assets, provide the assets base that countries rely tenth for natural capital and about a quarter for produced on to produce GDP capita from year to year. capital. In per capita terms, total wealth stood at $168,580 per person in 2014 versus $128,929 in 1995. Human Given the advantages of wealth accounting over annual capital wealth stood at $108,654 per person in 2014 versus earnings measures to measure losses in earnings due $88,874 in 1995. As will be shown in subsequent sections to gender inequality, we rely in this note on research of this note, inequality in human capital and total wealth recently completed by the World Bank on the Changing between countries is high. In high income OECD countries, Wealth of Nations study (Lange et al., 2018). Building on total wealth per capita is above $700,000, and human two previous reports (World Bank, 2006 and 2011), the capital wealth is at close to $500,000 per person. This is Changing Wealth of Nations 2018 study covers the period more than 90 times the levels in low income countries where 1995 to 2014. It includes not only estimates of produced human capital wealth is at $5,564 per person. capital and natural capital, as did previous reports, but also estimates of human capital following the approach At the global level, the dynamics of human capital wealth suggested by Jorgensen and Fraumeni (1992a, 1992b). accumulation are driven by shifts in OECD and upper- The estimations of human capital are based on household middle income countries simply because those countries survey data. They represent a significant improvement account for 87 percent of global wealth (65 percent for the over past estimates where total wealth included a large OECD alone). The proportions are even larger for human unexplained residual called ‘intangible capital’. This residual, capital wealth. In these countries, the share of human it turns out, consists for the most part of human capital. By capital wealth in total wealth has fallen slightly in recent measuring the shares of human capital wealth associated years in part because labor earnings as a share of GDP have to men and women at the country level, the methodology declined in OECD countries due to technological change, enables us to estimate lifetime earnings losses due to stagnating wages, and in some countries a reduction in the gender inequality. share of the population in the labor force due to ageing. By contrast, for low income and lower middle-income BASELINE ESTIMATES OF countries, the share of human capital wealth in total wealth is increasing. Many of these countries are experiencing a GLOBAL WEALTH demographic transition, and are reaping the benefits of the demographic dividend as population growth rates slow, The methodology for estimating human capital wealth as and the population is becoming better educated. While well as the losses due to gender inequality is explained in substantial progress has been achieved to close gender gaps Appendix 2. Before presenting results on losses in wealth in educational attainment at the primary level, the returns due to gender inequality, this section presents baseline to education are often larger at higher levels of schooling. estimates of human capital and total wealth from Lange et At those levels, gender gaps in educational attainment al. (2018). Table 1 provides global estimates in absolute value remain, especially in low income countries. Furthermore, as and per capita terms. The analysis is based on data for 141 countries achieve higher levels of economic development, countries accounting for more than 95 percent of the world’s human capital wealth dominates. At lower levels of population. All estimates are in constant US dollars of 2014. economic development, natural capital continues to account for a larger share of wealth. MAY 2018 | THE COST OF GENDER INEQUALITY: UNREALIZED POTENTIAL: THE HIGH COST OF GENDER INEQUALITY IN EARNINGS | 4 Table 1: Baseline Estimates of Global Wealth, 1995-2014 1995 2000 2005 2010 2014 Total wealth, Trillions, constant 2014 $ Total wealth 689.9 790.9 889.1 1,024.7 1,143.2 Produced capital 164.8 187.9 226.9 269.0 303.5 Natural capital 52.5 54.2 70.0 97.2 107.4 Human capital 475.6 552.7 595.4 661.1 736.9 Net foreign assets -2.9 -3.9 -3.3 -2.6 -4.6 Population (billions) 5.35 5.73 6.09 6.47 6.78 Per capita wealth, constant 2014 $ Total wealth 128,929 138,064 145,891 158,363 168,580 Produced capital 30,793 32,801 37,237 41,570 44,760 Natural capital 9,803 9,463 11,487 15,019 15,841 Human capital 88,874 96,478 97,707 102,170 108,654 Net foreign assets -540 -678 -539 -395 -676 Share of total wealth Total wealth 100% 100% 100% 100% 100% Produced capital 24% 24% 26% 26% 27% Natural capital 8% 7% 8% 9% 9% Human capital 69% 70% 67% 65% 64% Net foreign assets 0% 0% 0% 0% 0% GLOBAL LOSSES FROM wealth for women today globally and the losses in human capital wealth due to gender inequality. Globally, in 2014 GENDER INEQUALITY women accounted for 38 percent of human capital wealth versus 62 percent for men. These are also essentially the Estimations of human capital wealth are done separately for proportions observed for upper middle and high-income men and women (see the appendix to this note and Wodon, OECD countries which account for the bulk of human 2018, for details). Losses in human capital wealth due to capital wealth. In low income and lower-middle income gender inequality are calculated in a simple way. Denote a countries, women account for only a third or less of human country’s human capital wealth from men’s and women’s capital wealth. In those countries, gender inequality thus expected future earnings as HCM and HCW, respectively. generates in proportional terms a larger loss in human capital The adult population of men and women are denoted by wealth, and thereby in total wealth, as will be discussed POPM and POPW. Human capital wealth per adult man and further below. woman are defined as hcM=HCM/POPM and hcW=HCW/ POPW. Gender equality is assumed when adult men and How large are the potential losses in wealth resulting from women achieve the same future expected earnings. In other gender inequality globally? As shown in Table 2, women’s words, in countries where hcW is below hcM (this is virtually human capital could increase from $283.6 trillion to $453.2 the case for all countries), human capital for women would trillion with gender equality. This represents a potential loss increase to reach hcM. The loss in human capital wealth in global wealth of $160.2 trillion. The estimated increase from gender inequality is measured as (hcM-hcW)×POPW1. in human capital wealth from the base is 21.7 percent in As discussed in Box 1, there are clear limitations to this 2014, and for total wealth (including natural and produced approach, but the approach has the merit of being simple and capital as well as net foreign assets), the increase in wealth is it helps in providing an order of magnitude for the losses in estimated at 14.0 percent. On a per capita basis (including human capital potentially associated with gender inequality. not only the adult population but also children), gender inequality could lead to a loss in wealth of $23,620 per Table 2 provides estimates of the shares of human capital person. These potential losses are clearly large. They In very rare cases when hcW is larger than hcM, we could raise hcM to the level of hcW, but for standardization we instead adjust hcW downwards. These rare cases do not make any meaningful 1 difference to the overall results however. 5 | THE COST OF GENDER INEQUALITY: UNREALIZED POTENTIAL: THE HIGH COST OF GENDER INEQUALITY IN EARNINGS | MAY 2018 underscore the benefits that could be reaped globally from equality in many countries over time, which makes the achieving gender equality. losses smaller. But in addition, human capital in high income countries has been declining slightly in recent years Over time, the estimate of the total wealth lost due to due among others to ageing and a reduction in the share gender inequality increases from $123.2 trillion in 1995 to of labor income in GDP. This in turn contributes to a small $160.2 trillion in 2014, which is about twice the value of reduction of the losses from gender inequality over time as global GDP. This increase comes from population growth, a share of the baseline wealth estimates. as well as higher standards of living. But other factors that affect human capital wealth at the country and regional level How do our results compare to previous studies? also play a role, including factors that affect the share of Comparisons can be made for both the estimates of (i) labor earnings in GDP over time. gender shares in earnings which are key for the estimation of the losses from gender inequality; and (ii) the magnitude As a share of baseline wealth, losses from gender inequality of the losses associated with gender inequality. tend to be slightly lower in 2014 than in 1995. This is in part because there is a (slow) movement towards more BOX 1: LIMITATIONS OF THE METHOD USED TO COMPUTE LOSSES IN HUMAN CAPITAL WEALTH The estimation of the losses in human capital wealth provided in this note simply assumes that women could work and earn as much as men. The estimation does not consider potential effects on men of rising earnings and hours worked for women. We do not account for the fact that men’s earnings may decrease if women become better educated and have access to the same employment opportunities as men (for example, resulting from reductions in occupational segregation). We also assume that women can allocate more time to labor market work without a negative impact on men’s working hours, therefore not considering the possibility of men having to allocate more time to household chores or unpaid care. Women tend to do most of the domestic work, especially in developing countries. As women work more hours in paid employment, they may have less time for unpaid domestic work, which could affect the number of hours that men may be able to spend in paid employment, depending on options for elderly, child, or other care services available to households. Many other effects could be at work as women catch up with men in earnings. Here, for simplicity, we only compute how much more human capital countries would gain if women had the same lifetime earnings profile as men without any decrease in men’s earnings. In that sense, the estimate could be considered an upper bound of the losses from gender inequality, because we do not factor in the potential general equilibrium impact of higher work and earnings for women on men or the labor market more generally. However, the estimation could also be a lower bound of the losses. Indeed, higher earnings for women could lead to more economic activity with positive multiplier effects on the economy and thereby wages. Furthermore, if systems for the provision of care to family members were expanded, a substantial share of the time now allocated to unpaid care could become paid care work. The literature also suggests that as countries develop and women join the labor market or work longer hours, this may primarily reduce free time and time spent on domestic chores. Overall, especially through multiplier effects, unleashing women’s earnings potential could generate even larger earnings and human capital gains for both men and women than suggested in this note. We also do not account for intergenerational benefits from unleashing women’s earnings potential through better education, health, and employment opportunities for their children. In subsequent work on the cost of gender inequality, we will explore these issues in more details to look at potential paths for countries to end gender inequality and the implications that these paths may have through general equilibrium effects for the estimates of the losses from gender inequality. MAY 2018 | THE COST OF GENDER INEQUALITY: UNREALIZED POTENTIAL: THE HIGH COST OF GENDER INEQUALITY IN EARNINGS | 6 • Gender shares: Previous studies have focused on or 14 percent of our baseline estimate of global wealth. gender shares in GDP, while we estimate gender Our estimate is larger in absolute value simply because shares in human capital wealth. Still, given that wealth is larger than GDP. In 2014, global wealth is both approaches are based on earnings data, they estimated at $1,143 trillion for the 141 countries included should generate similar gender shares. This is indeed in our analysis, while global GDP for those countries is the case. The gender shares of GDP reported by estimated at $75 trillion5. Wealth is thus 15 times larger the McKinsey Global Institute (2015) are similar than GDP. But in proportionate terms, our estimate to ours2. The same conclusion is reached when is more conservative. We suggest a loss of 14 percent comparing globally our estimates of women’s share of baseline wealth. This is smaller than the loss of 26 of human capital wealth to estimates of women’s percent of GDP suggested in the McKinsey Global contribution to GDP from the World Economic Institute study. As discussed in Wodon (2018), various Forum’s Gender Gap Report (2017). Broadly, there is factors could account for the difference in proportional alignment at least at the global and regional levels3. impacts, including the fact that our estimates of human capital wealth account for the labor share in • Magnitude of the losses: The McKinsey Global Institute GDP. Still, both types of estimates are only meant (2015) study reports potential gains in GDP from a to give orders of magnitude of the potential losses ‘full potential’ scenario of $28 trillion or 26 percent from gender inequality as opposed to very precise of GDP in 2025 versus a ‘business-as-usual’ scenario values, and both types of estimates suggest that the without gender equality4. We report losses in human losses from gender inequality are indeed very large. capital wealth from gender inequality of $160 trillion Table 2: Global Losses in Wealth from Gender Inequality, 1995-2014 1995 2000 2005 2010 2014 Global wealth, Trillions, constant 2014 $ Baseline gender shares of human capital Men’s share of human capital 63% 63% 62% 61% 62% Women’s share of human capital 37% 37% 38% 39% 38% Human capital wealth by gender Human capital, men 301.2 349.1 371.6 405.5 453.2 Human capital, women 174.4 203.6 223.8 255.6 283.6 Loss from gender inequality Counterfactual human capital, women 297.6 344.5 366.4 398.4 443.8 Increase in human capital 123.2 140.9 142.6 142.8 160.2 Loss as share of baseline human capital 25.9% 25.5% 24.0% 21.6% 21.7% Loss as share of baseline total wealth 17.9% 17.8% 16.0% 13.9% 14.0% Per capita wealth, constant 2014 $ Baseline global wealth Human capital per capita, men 56,290 60,940 60,980 62,672 66,832 Human capital per capita, women 32,584 35,538 36,727 39,498 41,823 Loss from gender inequality Loss in human capital per capita 23,030 24,603 23,391 22,068 23,620 Source : Wodon (2018). 2 Our estimate of women’s share of human capital wealth at 38 percent globally in 2014 is close to McKinsey’s estimate of women’s contribution to GDP at 37 percent. Gender shares are broadly similar at the regional level as well. For East Asia and the Pacific, women’s share of human capital wealth is 35 percent, while McKinsey reports women’s contributions to GDP of 41 percent for China and 34 percent for the rest of the region. In Europe and Central Asia, women’s share of human capital is at 39 percent in this study, versus 38 percent for their share in GDP in Western Europe and 41 percent for Eastern and Central Europe in the McKinsey study. In Latin America and the Caribbean, our share for women is at 44 percent versus 33 percent for McKinsey. In the Middle East and North Africa, we are at 27 percent versus 18 percent for McKinsey. The shares for North America are virtually the same at 41 percent and 40 percent. In South Asia, our share is at 19 percent versus 17 percent for India and 24 percent for other countries in the McKinsey study. Finally, for sub-Saharan Africa, we have the same share for women at 39 percent. 3 As to whether one set of approaches is better than another at the country level to estimate women’s shares of GDP or human capital wealth, this is a question that needs to be investigated further. The results may vary from one country to another depending on the quality of the underlying data. But for broad aggregates as reported here, the underlying shares are fairly similar. 7 | THE COST OF GENDER INEQUALITY: UNREALIZED POTENTIAL: THE HIGH COST OF GENDER INEQUALITY IN EARNINGS | MAY 2018 ANALYSIS BY REGIONS ANALYSIS FOR COUNTRIES The losses in human capital wealth from gender inequality AT DIFFERENT LEVELS OF differ between regions and between countries classified by broad income groups. Tables 3 provides the estimates for DEVELOPMENT overall losses in human capital wealth and wealth per capita for seven regions: East Asia and the Pacific, Europe and Losses from gender inequality also differ between countries Central Asia, Latin America and the Caribbean, the Middle ranked by income groups, defined according to the World East and North Africa, North America, South Asia, and Bank classification (low income, lower middle income, finally sub-Saharan Africa. upper middle income, and high income). In this section, we differentiate between high income OECD and other high- Consider the estimates for 2014. The largest total losses in income countries. The latter group includes several oil- wealth from gender inequality are observed for East Asia producing countries from the Middle East. Table 4 provides and the Pacific, North America, and Europe and Central the estimates for these five income groups. Asia, in each case at between $40 trillion and $50 trillion. This is because many of the countries in these regions are Consider again the estimates for 2014. In absolute terms, high income or upper middle income, and thereby they the largest total losses in wealth are observed for high concentrate much of the world’s human capital wealth. In per income OECD countries and upper-middle income capita terms as well, the losses are larger in those regions. But countries (which include China). Together these two the losses in other regions are substantial too, including in groups of countries experience a loss of $140.2 trillion in comparison to current levels of development. For example, in human capital wealth due to gender inequality. The other South Asia, the losses from gender inequality are estimated countries together lose $20 trillion in human capital wealth. at $9.1 trillion. In sub-Saharan Africa, the losses are at $2.5 But again, in percentage terms from the base, the picture trillion. This is the smallest estimate across regions. However, is different. Low income countries lose 15.1 percent of as a share of initial wealth, the losses from gender inequality their base level of wealth (including all types of capital) in sub-Saharan Africa represent 11.4 percent of the base under gender inequality, which is slightly larger than the regional wealth, which is larger than the loss in Latin America increase for the world, at 14.0 percent as shown in Table 2. and the Caribbean and especially the Middle East and North Note also that losses from gender inequality are lower in Africa in part because of high levels of natural capital from proportional terms from the base in high-income non- sub-soil assets (especially oil) in that region. The loss in total OECD countries, in part because many of these countries wealth from the base with gender inequality is highest in have substantial oil reserves and thereby higher levels of South Asia, because this is also the region with the lowest natural capital in their baseline wealth. initial share of women in human capital. 4 The McKinsey Global Institute study also considered a best-in-region scenario in which all countries would match the rate of improvement of the best-performing country in their region. This would add $12 trillion in annual GDP by 2025. 5 Our estimation includes a larger set of countries than included in the McKinsey Global Institute study, although this does not make a very large difference for estimates of global losses given that most of the wealth, especially for human capital wealth, remains concentrated in upper middle income and high-income countries and the fact that these countries are also included for the most part in other studies including that by the McKinsey Global Institute. MAY 2018 | THE COST OF GENDER INEQUALITY: UNREALIZED POTENTIAL: THE HIGH COST OF GENDER INEQUALITY IN EARNINGS | 8 Table 3: Losses from Gender Inequality by Region, 1995-2014 1995 2000 2005 2010 2014 ($ 2014) ($ 2014) ($ 2014) ($ 2014) ($ 2014) East Asia & Pacific Loss in human capital ($ trillions) 34.2 35.8 37.7 42.1 49.9 Loss in human capital per capita ($) 18,627 18,450 18,663 20,130 23,253 % loss in total wealth 24.5% 22.1% 20.8% 17.1% 16.6% Europe & Central Asia Loss in human capital ($ trillions) 32.4 36.3 37.2 38.8 41.6 Loss in human capital per capita ($) 39,892 44,511 45,045 46,261 48,884 % loss in total wealth 14.3% 14.8% 13.7% 13.0% 13.3% Latin America & Caribbean Loss in human capital ($ trillions) 7.3 5.9 6.5 6.7 6.7 Loss in human capital per capita ($) 15,500 11,558 11,945 11,468 10,940 % loss in total wealth 14.3% 10.5% 10.2% 8.8% 7.9% Middle East & North Africa Loss in human capital ($ trillions) 1.6 2.1 2.4 2.7 3.1 Loss in human capital per capita ($) 9,275 11,261 11,220 11,150 11,757 % loss in total wealth 10.2% 11.8% 9.9% 7.7% 7.4% North America Loss in human capital ($ trillions) 43.4 55.1 51.3 43.3 47.2 Loss in human capital per capita ($) 146,791 175,923 156,600 126,052 133,299 % loss in total wealth 18.8% 19.5% 16.3% 13.3% 13.5% South Asia Loss in human capital ($ trillions) 3.3 4.6 6.5 7.4 9.1 Loss in human capital per capita ($) 2,664 3,383 4,374 4,613 5,405 % loss in total wealth 28.8% 32.2% 35.0% 29.4% 29.4% Sub-Saharan Africa Loss in human capital ($ trillions) 1.1 1.1 1.0 1.9 2.5 Loss in human capital per capita ($) 2,016 1,927 1,435 2,480 2,914 % loss in total wealth 7.6% 8.8% 6.3% 9.8% 11.4% Source : Wodon (2018). 9 | THE COST OF GENDER INEQUALITY: UNREALIZED POTENTIAL: THE HIGH COST OF GENDER INEQUALITY IN EARNINGS | MAY 2018 Absolute losses in human capital wealth from gender growth rates in human capital for women tend to be higher inequality are (much) higher in high income than in low for lower income countries. Indeed, observations in the income countries simply because the levels of wealth on scatter plot for lower income countries tend to be located which losses are applied are higher in high income countries. further away from the diagonal than for higher income Is there convergence over time in estimates of human capital countries. There appears to be some level of convergence wealth for women across countries? Figure 1 displays a in human capital wealth for women with poorer countries scatter plot for the levels of women’s human capital wealth (slowly) catching up, although this is not always the case (see per capita in 1995 (on the horizontal axis) and in 2014 (on Box 2 for a more detailed discussion). the vertical axis). Since estimates are in logarithms, the difference between the values for 2014 and the diagonal The fact that low income countries lie so far behind high represents approximately the cumulative growth observed income countries in levels of human capital wealth suggests over two decades. that programs and policies are needed to raise the earnings potential of women (and men). Many of the programs Most countries lie above the diagonal, suggesting that an and policies discussed in the next two sections have the overwhelming majority of countries benefited from an potential not only to move countries closer to equality in increase in human capital wealth per capita for women earnings between men and women, but also to raise those between 1995 and 2014. However, a few countries have lost earnings more generally. ground, often due to a conflict or other shock. In addition, Table 4: Losses from Gender Inequality by Income Group, 1995-2014 1995 2000 2005 2010 2014 ($ 2014) ($ 2014) ($ 2014) ($ 2014) ($ 2014) Low income countries Loss in human capital ($ trillions) 0.4 0.5 0.6 0.8 1.1 Loss in human capital per capita ($) 1,335 1,406 1,415 1,675 2,052 % loss in total wealth from base 11.5% 13.5% 13.8% 14.2% 15.1% Lower-middle income countries Loss in human capital ($ trillions) 6.8 7.6 9.4 11.0 13.5 Loss in human capital per capita ($) 3,407 3,472 3,958 4,275 4,967 % loss in total wealth from base 19.2% 20.7% 20.4% 18.1% 19.1% Upper-middle income countries Loss in human capital ($ trillions) 11.2 11.3 16.1 20.9 26.5 Loss in human capital per capita ($) 6,032 5,764 7,872 9,800 12,067 % loss in total wealth from base 11.8% 10.0% 11.9% 10.4% 10.7% High income non-OECD Loss in human capital ($ trillions) 2.7 3.6 3.8 4.7 5.4 Loss in human capital per capita ($) 10,637 14,047 14,378 17,021 18,672 % loss in total wealth from base 6.5% 8.6% 7.4% 7.1% 7.0% High income OECD Loss in human capital ($ trillions) 102.2 117.9 112.6 105.4 113.7 Loss in human capital per capita ($) 108,593 121,735 112,859 102,567 108,631 % loss in total wealth from base 19.8% 19.8% 17.3% 15.2% 15.3% Source: Wodon (2018). MAY 2018 | THE COST OF GENDER INEQUALITY: UNREALIZED POTENTIAL: THE HIGH COST OF GENDER INEQUALITY IN EARNINGS | 10 INVESTING IN HUMAN wage gap for adults is also due to differences in educational attainment between men and women, which are often CAPITAL THROUGHOUT themselves due in part to deeply entrenched social norms (see Box 3 on child marriage as an example which continues THE LIFE CYCLE to be highly relevant today). But other factors also play a role, including gender discrimination in labor markets and Why are there large differences between men and women occupational sex segregation which are themselves driven in in human capital wealth? The reasons are multiple, but in a part by social norms. While gender gaps in education have stylized fashion, two factors probably stand out. First, men been reduced in recent decades, these other factors leading have higher labor force participation rates than women and to gender gaps in earnings remain prevalent. they tend to work more hours in paid work. Women tend to work on average more hours than men overall, but a While programs and policies that could reduce the wage gap much larger share of this effort is dedicated to unpaid work by sex in terms of both earnings and labor force participation (household chores, care and work on household farms or are discussed in the following section and will also be detailed in household enterprises), hence they tend to have lower in subsequent notes, it may be useful to outline first how earnings. Second, men tend to earn more than women per broader investments in women (and men) along the life cycle hour of work. Although there has been progress towards could help boost human capital wealth accumulation more reducing inequality in educational attainment between generally. A particular emphasis is needed on interventions boys and girls over the last two decades, part of the gender from (pre-)birth to adolescence. FIGURE 1: CONVERGENCE IN WOMEN’S HUMAN CAPITAL WEALTH PER CAPITA 6.00 Human Capital Wealth Per Capita in 2014 5.50 5.00 (Log, US$ 2014) 4.50 4.00 3.50 3.00 2.50 2.50 3.00 3.50 4.00 4.50 5.00 5.50 6.00 Human Capital Wealth Per Capita in 1995 (in Log, US$) 11 | THE COST OF GENDER INEQUALITY: UNREALIZED POTENTIAL: THE HIGH COST OF GENDER INEQUALITY IN EARNINGS | MAY 2018 BOX 2: CONVERGENCE AND OTHER FACTORS AFFECTING HUMAN CAPITAL WEALTH Growth models can be estimated to analyze factors that may affect human capital wealth. In Nayihouba and Wodon (2018), the dependent variables are the growth rates in human capital wealth per capita estimated separately for women and men. Apart from the initial level of human capital wealth, independent variables include the average years of schooling of the adult population and life expectancy at birth, as well as other variables related to trade, government spending, investment, and inflation. Given that the theoretical model predicts that the growth rate of the population, the working age population, and the labor force may all affect human capital wealth per capita, these variables are also included in the regressors. The results suggest convergence in that countries with lower levels of human capital wealth tend to have higher growth rate. Higher rates of population growth are associated with slower growth in human capital wealth, while growth in the labor force has the opposite effect. Average years of schooling and life expectancy also have a positive effect on growth in human capital wealth per capita. When adding macroeconomic variables, familiar results are obtained, in that inflation is associated with slower rates of growth of human capital wealth, while open economies are associated with higher growth when effects are statistically significant. None of these results are surprising, but they point to the importance of investments in education and health and to the role that demographic factors and labor markets play. How can the earnings potential and thereby the human • Step 2. Ensuring that all students learn—by building capital wealth of women be increased? A few years ago, stronger systems with clear learning standards, good the World Bank (2010) developed a simple conceptual teachers, adequate resources, and a proper regulatory framework—Skills Toward Employment and Productivity environment. As noted in the recent World Development or STEP — to help policymakers, analysts, and researchers Report on education (World Bank, 2017), much of the think about interventions that could enhance labor world is experiencing a learning crisis. Key decisions about productivity and growth. Given that human capital wealth education systems involve how much autonomy to allow is based on measures of earnings, the framework, while not and to whom, accountability from whom and for what, specific to women, is relevant. The framework focuses on five and how to assess performance and results, including by interlinked steps in a person’s life during which it makes sense paying attention to gender gaps not only in educational to invest in human capital for better jobs and productivity: attainment, but also in learning performance for specific • Step 1. Getting children off to the right start—by subjects and reducing unconscious bias in curricula. developing the cognitive, emotional, and behavioral skills conducive to high productivity and flexibility in the work • Step 3. Building job-relevant skills that employers environment through early child development (ECD), demand—by developing the right incentive framework emphasizing nutrition, stimulation, and basic cognitive for both pre-employment and on-the-job training skills, all of which are affected by gender norms early programs and institutions (including in higher education). on in life. Research shows that handicaps built early in Successful experiences show that public and private life – for example in the case of chronic malnutrition, efforts can be combined to achieve relevant and are difficult to remedy later and that effective ECD responsive training systems. Gender gaps in specific programs can have a very high payoff. In some countries skills must be addressed, especially at the secondary in South Asia for example, gender gaps already appear and tertiary levels where girls are less likely than boys to in ECD, as is the case when chronic malnutrition specialize in topics related to STEM (Science, Technology, (stunting) rates are higher for girls than for boys. Engineering and Mathematics). This should help reduce occupational segregation and increase productivity. MAY 2018 | THE COST OF GENDER INEQUALITY: UNREALIZED POTENTIAL: THE HIGH COST OF GENDER INEQUALITY IN EARNINGS | 12 BOX 3: LOSSES IN EARNINGS AND HUMAN CAPITAL WEALTH DUE TO CHILD MARRIAGE Child marriage is defined as a marriage or union before the age of 18. The practice affects mostly girls. It has been declining over time, but especially in sub-Saharan Africa, many girls continue to marry as children (Le Nestour et al., 2018). Child marriage has negative impacts on a wide range of outcomes and therefore large economic costs. In the case of earnings, the impact of child marriage on labor force participation may not be very large. However, because child marriage leads girls to drop out of school, it affects expected earnings. Savadogo and Wodon (2018) suggest that controlling for other factors, child marriage leads to a loss in earnings for women in adulthood of nine percent on average for women who married as children in 15 countries with relatively high levels of child marriage. Most of these losses are due to lower educational attainment as opposed to higher fertility rates which may affect labor force participation. Given that human capital wealth estimates are based on expected earnings, child marriage also leads to substantial losses in human capital wealth. • Step 4. Encouraging entrepreneurship and innovation— livelihoods. In the next section, the emphasis is on lessons by creating an environment that encourages investments learned from a brief literature review on interventions that in knowledge and creativity. Evidence suggests that have proven successful in enabling women to acquire and keep this requires innovation-specific skills (which can be good jobs, whether as employees or through self-employment. built starting early in life) and investments to help connecting people with ideas (say, through collaboration between universities and private companies) as well as IMPROVING EMPLOYMENT risk management tools to facilitate innovation. Lack of networks and knowledge are important constraints for OPPORTUNITIES FOR female entrepreneurship, as is limited access to finance. Women-led enterprises also tend to be concentrated WOMEN: LESSONS FROM in the retail and service sectors where profits and growth opportunities are lower, and rarely in mining, THE LITERATURE construction, electronics or software, for example. Within an economic analysis framework, a woman’s • Step 5. Matching the supply of skills with the decision to participate in the labor force is fundamentally demand— by moving toward more flexible, efficient, determined by two sets of factors: those that affect her and secure labor markets. Avoiding rigid job protection reservation wage – the wage at which she is willing to enter regulations while strengthening income protection the labor market, and those that affect the wage she can systems, complemented by efforts to provide earn in the market (Winkler, 2016). The reservation wage information and intermediation services to workers and varies directly with the availability of market substitutes for firms, is the final complementary step transforming household production and technology; inversely with the skills into actual employment and productivity. This also husband’s (or other earners’) income; and is affected by the has gender implications as narrow solutions focusing presence of children and broader social norms regarding only for example on the supply of skills are rarely fertility, appropriate roles of women and men, and decision- effective; multi-dimensional comprehensive approaches making. A woman’s wage in the market depends on her considering both supply and demand are required. human capital, her labor force experience, especially her firm-specific human capital, and the existing demand This simple framework emphasizes that investments for her labor. Women’s labor force participation is also throughout a person’s life are needed to create human capital affected by labor market, fiscal, and family policies as well wealth, and thereby ensure that individuals have adequate as employer policies. Across countries, additional factors 13 | THE COST OF GENDER INEQUALITY: UNREALIZED POTENTIAL: THE HIGH COST OF GENDER INEQUALITY IN EARNINGS | MAY 2018 include non-economic ones (political ideology, religion, review of time use surveys from 19 countries (Rubiano culture), stages in economic development, and industrial and Viollaz, 2018) shows significant differences in the way mix with different relative demands for female labor in the women and men allocate their daily time between leisure, private informal, private formal, and public sectors. unpaid work (household chores and child/elderly care) and market work. Women spend on average 5 hours in unpaid Harnessing the returns from increased female labor force work and 2.3 hours in market work while men spend 5 participation into activities generating more income means hours in market work and 1.9 hours in unpaid work. Similar levelling the playing field and addressing the potentially findings have been found in previous work using time use difficult reallocation of time between paid employment and data for sub-Saharan Africa (Blackden and Wodon, 2006). other activities as well as persistent and pervasive gender Recognizing, reducing, and redistributing unpaid work differences in productivity and earnings across different would thus free a significant amount of time for women to sectors and jobs. Men’s and women’s jobs differ across participate in market work. sectors, occupations, types of jobs, and firms. At home, access to basic infrastructure services (water, The World Development Report on gender (World Bank, electricity, energy), as well as child and elderly care services 2012) posited that these differences stemmed from three can free women’s time. The role of infrastructure in freeing main factors: (i) unequal distribution of time use and care productive time for women has long been recognized responsibilities between men and women and between (Estache and Wodon, 2014). Rural electrification for households and public/private service provision; (ii) unequal example contributes to women’s economic empowerment access to and control over productive assets (particularly by increasing the length of the work day, reducing time for land, credit, insurance and savings but also key skills); and housework and fuel collection, and providing home-based (iii) market and institutional failures (access to information business opportunities. This is especially the case when and networks, legal and fiscal impediments, restrictive social gender biases in the family and local economy are also norms). These differences may affect all women, whether addressed, given interdependence in women and men’s they are wage workers, farmers, or self-employed workers/ time allocation decisions (van de Walle et al., 2013). The entrepreneurs. These differences also often mutually same is true for access to water. In Morocco, a project reinforce each other and lead to productivity traps for aimed to reduce the burden of girls traditionally involved in women. This is costly not only for them, but also to their fetching water to improve their school attendance. In the household, their community, and society as the estimates project’s areas, girls’ school attendance increased by 20 of the losses in human capital wealth from gender inequality percent in four years (World Bank, 2003). shown earlier demonstrate. In addition, these differences represent a serious disincentive to investments in the women For child care, Reimo et al. (2017) review the evidence of tomorrow. on the impact of providing child care and early education services. They find that the provision of these services This section discusses some of the policies that could help in Latin America increases female employment by 10 reduce the inequality in lifetime earnings between men and to 30 percent. Public provision of affordable and quality women. Given limitations of space, the objective is not to child care is especially important for women’s labor be exhaustive, but rather to point to some of the findings force participation, but there is also a role for employer- emerging from the literature on what works to reduce supported childcare provided that the costs of provision do gender inequality, acknowledging that various policies may not affect negatively women’s employment opportunities. be more relevant in some countries than in others. Examples Partnerships and collaboration between the public and of potential policies to be adapted to country context are private sectors and civil society organizations can help in provided in Table 5. this regard (International Finance Corporation, 2017). Interventions that make it easier for women to get to ADDRESSING TIME USE CONSTRAINTS work can also be beneficial. While women tend to be responsible for a disproportionate share of their household’s Virtually every society has a division of labor based on transport needs, they tend to have more limited choices gender norms – typically with women specializing in for mobility, in terms of mode and distance. A combination reproductive work and men in productive work. A recent of inadequate mobility choices (including slower travel MAY 2018 | THE COST OF GENDER INEQUALITY: UNREALIZED POTENTIAL: THE HIGH COST OF GENDER INEQUALITY IN EARNINGS | 14 Table 5: Examples of Interventions to Address Constraints on Women’s Paid Work Constraints/Type of work Wage employees Farmers Entrepreneurs/Self-employed 1. Time use constraints Basic Infrastructure Access to basic infrastructure (cooking energy, water, electricity) Access to safe and affordable transportation Childcare Access to quality, affordable, publicly sponsored or employerprovided childcare Laws & technology Workplace flexibility including Time saving technology Time saving technology parental leave 2. Access to productive assets Land - Joint titling - Skills Bundled training (technical and managerial) including socio-emotional skills (persistence), and asset-specific training Micro-credit (self-employed) In-kind and cash grants Credit (Small & Medium Alternative collateral: moveable assets, payment history, - Enterprises) psychometric tests Digital finance/savings and Direct payments to accounts - Individual saving accounts payments systems Other financial services Bundled financial services for risk management including insurance products for business and health needs among others Banking Mobile/web banking and simplification of KYC (Know your customer) rules 3. Market and institutional failures Information Payment transparency Innovations in rural extension Returns to traditionally Workers’ rights Engagement in value chains male-dominated sectors Social capital Expanding social networks: mentorship and sponsorship, role models Legal frameworks Removing gender differences in business, labor and family laws, enforcing existing laws supporting gender equality Taxation Individual income tax - Differential VAT Social norms Preventing and mitigating gender-based violence Building aspirations and self-confidence Source: Authors. options and off-peak travel when frequencies are low) monitoring tools (with mobile technology and witness with more complex travel needs leads to slower travel bystander interventions), and information measures to speed and thereby smaller travel distances for women, foster behavior change (through education campaigns, resulting in limited access to economic opportunities and increased law enforcement, and public-sector unions) are essential services. Studies in both developing and developed all positive measures. On-going experiments in several countries show a negative correlation between commuting countries (such as Brazil and Pakistan) as well as the time and women’s participation in the labor force (see development of alternative transportation modes (ride- for example Black et al., 2014 for the United States). An sharing) should shed light on what works and what are the increase of one minute in commuting time in metropolitan constraints. Ride hailing platforms like Didi and Uber also areas is associated with a 0.3 percentage point decline in provide opportunities for women’s employment, in terms of women’s labor force participation. flexibility, mobility and personal safety, but discrimination remains (see Accenture and International Finance Security concerns also affect women’s travel. Policy Corporation, 2018). and program interventions to enhance security through At work itself, parental leave, flexible schedules and mode physical infrastructure investments (lighting in stations, of work, and legislation on retirement ages can all make design of buses and trains, cameras and alarm systems), a difference. As noted under the Women, Business, and developing and testing new security reporting and the Law indicators, policies that help workers balance paid 15 | THE COST OF GENDER INEQUALITY: UNREALIZED POTENTIAL: THE HIGH COST OF GENDER INEQUALITY IN EARNINGS | MAY 2018 work and family responsibilities include parental leave FACILITATING ACCESS TO PRODUCTIVE ASSETS (which can be taken by either parent). The opportunity for workers to return to their pre-leave work or employer Especially in low income countries, women’s employment increases labor force participation and helps workers retain is informal, with self-employment being the most common firm-specific human capital. The so-called father’s quota in type of work, and a large share of women still work in the Nordic countries provides an incentive for fathers to take agricultural sector. Women farmers and entrepreneurs their leave or lose it, and to share in the child care. Work consistently produce less and generate less income than their place flexibility, either through part-time work, flexible male counterparts (World Bank and ONE, 2014, Campos hours, compressed schedules (“flextime”) or through and Gassier, 2017). This reflects both unequal access to telecommuting/home-based work also help workers inputs and lower returns to these inputs. balance the demands of paid work and family responsibility. For both leave and flexible work arrangements, it is For female farmers, access to, and control over good quality important to ensure the participation of both women and land are especially critical for agricultural investment and men and to calibrate the generosity of leave/flexibility to rural household welfare. Yet statutory and customary land minimize potential downsides for women in terms of slower tenure systems often disadvantage rural women, who are career progression or occupational segregation. less likely to control land than rural men. Women’s tenure insecurity reduces their investments in their land, thus In many developing countries, flexibility is only available undermining their productivity. Strengthening women’s through the informal sector and women tend to be land rights is key to addressing the issues undermining their concentrated in those jobs, which are often the only jobs productivity. For example, Rwanda is making joint ownership enabling them – at a high cost in foregone income – to the default option in its land titling program, which is balance income-generation and family responsibilities. In associated with greater productivity (Ali et al., 2014). the formal sector, ensuring that women and men can work until the same (retirement) age is particularly beneficial for Also important is the acquisition of soft technical and women who tend to have patchier market work histories managerial skills. For farmers, factors relating to land beyond and shorter employment spells than men, which means access itself help explain the gender gap. One of these that their retirement income is lower. Earlier retirement challenges relates to land size. In Ethiopia and Tanzania, ages for women can cast an additional penalty as do long women receive lower returns than men to an extra hectare vesting periods. of land. This could be due to lower quality of the land, but it could also be due to women’s relative difficulty in managing/ hiring farm labor or the application of other inputs across larger tracts of land. MAY 2018 | THE COST OF GENDER INEQUALITY: UNREALIZED POTENTIAL: THE HIGH COST OF GENDER INEQUALITY IN EARNINGS | 16 Financial exclusion also remains a barrier for many women more effective than just providing capital and technical skills. farmers and entrepreneurs. Micro-credit by itself is not High-quality business management training of significant sufficient for a transformative impact. As women are less duration (6 to 12 weeks) can have positive outcomes for likely to hold titles to their productive assets, they face poor female entrepreneurs, with improvements in business higher hurdles to secure loans for lack of suitable collateral. practices, leading to increased sales, profits, and survival Promising initiatives include the promotion of alternative rates. Demand-driven job services (plus vouchers/subsidies collateral through moveable asset registries, the use of to employers and child care/transport stipends for trainees) payment histories for services such as cell phones, and increase economic opportunities of young women, especially psychometric testing to assess lenders’ risk (Buehren et if they tackle discrimination and other barriers in the training al., forthcoming). In addition, as women may face larger and work environments. difficulties to keep business/farm and household finances separate, health insurance products help to avoid depleting SOLVING MARKET AND INSTITUTIONAL working capital when responding to family health needs FAILURES (Campos and Gassier, 2017). Market failures refer broadly to situations in which markets Given their time constraints, women are also more likely to do not lead to optimal resource allocations. Institutional prefer bundled products including insurance and financial failures refer to institutions not functioning properly and services (International Finance Corporation et al., 2015). therefore not achieving their missions. Both types of failures Secure (private) individual savings accounts, including in can be pervasive with potentially serious implications for the form of commitment accounts and liquid savings, have gender inequality, as a few examples help illustrate. positive outcomes for women across countries, ages and activities. Women still have an unmet demand for those Access to information to address occupational segregation and for entrepreneurs, they help protect specific business and pay gaps can help improve gender equality. Women funds. However, very poor women might be too poor to farmers tend to have less access to information about save without additional support (Buvinic and O’Donnell, farming technology and methods as extension services 2016). Bundled services including a relatively large (in-kind) are rarely designed to take their specificities (in terms of capital transfer, asset-specific training, technical assistance, time availability, types of crops, or access to inputs) into a stipend for one to two years, and health information/ account. Enabling women to shift to high value commercial insurance and life skills training have shown that they can crops shows promise in Africa. Access to information about help push very poor women out of poverty traps with positive potential returns for women in male-dominated fields can economic outcomes and increased savings. One example is help female entrepreneurs cross over and shift sectors the BRAC Ultra-poor Graduation program (Banerjee et al., (Campos et al., 2015), provided they also get support 2015). More generally, innovative approaches such as the from male mentors in the field and can withstand sexual Women Entrepreneurship Finance Initiative can advance harassment and barriers to access credit. women’s entrepreneurship by increasing access to the finance, markets, technology, and networks necessary to Access to social capital (networks, role models, and start and grow a business. mentorship) also matters. Business associations, networks, mentors, and role models hold promise for both women Acquiring managerial and psychosocial skills is important entrepreneurs and farmers as they complement and for all women, but especially farmers and entrepreneurs. reinforce the effects of interventions such as business Women farmers may face additional hurdles than their male training, cash transfers and agricultural extension. The counterparts in hiring and supervising labor, or in using inputs complementarity seemingly arises from acquiring both such as fertilizers and pesticides correctly. information and social support, although we don’t know whether these measures are similar or work differently. For entrepreneurs, recent evidence points to the importance Self-help groups in particular foster increased solidarity of training combining soft skills (especially for young female between peers, independent financial decision-making, and entrepreneurs or in fragile and conflict-affected countries) greater respect for the women within their households and and managerial skills together with grants. This seems to be communities (Brody et al., 2015) 17 | THE COST OF GENDER INEQUALITY: UNREALIZED POTENTIAL: THE HIGH COST OF GENDER INEQUALITY IN EARNINGS | MAY 2018 Another important area for reform is legal and fiscal labor force participation can promote their empowerment frameworks. This includes labor market policies aimed and well-being, as well as the welfare of their children at ensuring equal opportunities in the labor market such (since mothers often control more spending related to as anti-discrimination laws and the elimination of laws children). However, the empirical relationship between restricting women’s labor force participation in some women’s employment and domestic violence is less sectors. It also includes laws about access to capital and clear-cut, depending on whether husbands perceive their justice, as noted in Women, Business and the Law reports. roles as breadwinners undermined (especially in case of Finally, it includes policies targeted at advancing women unemployment or when the deviance from gender norms to top positions (such as managerial and board diversity is too strong) and male co-workers perceive potential targets). These various laws are expected to positively displacement from female employees or female colleagues influence women’s labor force participation decisions and as “unsuitable”. The evidence is mixed: non-significant the type of employment they hold. relationship in Jordan (Lenze and Klasen, 2017), positive in India (Amaral et al., 2015 with increases in kidnappings, The structure of income tax policy creates a “second earner” sexual harassment, domestic violence and decreases in penalty if the family is considered the unit of taxation or dowry deaths; Paul, 2016), and negative in the United States if dependent credits or allowances are eliminated when a (Aizer, 2010 with the closing in the gender wage gap through spouse enters the labor market (Grown and Valodia, 2010). exogenous changes in labor demand in female-dominated On the other hand, earned income tax credits provide an industries). The direct and indirect costs of gender-based income subsidy for low-earner families and encourages violence to women and their children’s productivity could women in those families to enter the labor force. amount to several percent of global GDP (Hoeffler and Fearon, 2014). More rigorous evaluations of the impacts of Ensuring safety and preventing gender-based violence interventions for prevention, deterrence, and mitigation are at home, at work, and in public spaces is also essential. needed in this area to find the approaches that will work best. Appropriate laws are still lacking in many countries (Tavares and Wodon, 2018). There are also potential links between work and gender-based violence. Enhancing women’s MAY 2018 | THE COST OF GENDER INEQUALITY: UNREALIZED POTENTIAL: THE HIGH COST OF GENDER INEQUALITY IN EARNINGS | 18 CONCLUSION The objective of this first note in a series on the cost of gender inequality was twofold: (i) to demonstrate the economic cost from gender inequality in the case of earnings and human capital wealth; and (ii) to review some of the broad policies and specific interventions that could help achieve greater equality. The economic case for investing in girls and women is now very strong. Losses in human capital due to gender inequality are estimated at $160.2 trillion. On a per capita basis, gender inequality generates losses in wealth of $23,620 per person. By contrast, gender equality would raise the (changing) wealth of nations by 14.0 percent globally. The losses differ between regions and income groups since levels of human capital wealth also differ. To increase women’s earnings and human capital wealth, investments throughout the life cycle are needed, starting with early childhood development and learning in schools, and continuing with improved job opportunities in adulthood. The literature reviewed in this note was focused on job opportunities (other notes in the series will discuss earlier investments). Successful interventions can be implemented to address time use constraints, facilitate access to productive assets, and solving market and institutional failures that penalize women. Interventions need to be tailored in terms of age (young women face specific barriers and opportunities), poverty (very poor women need more than a single intervention) and type of participation (considering wage workers, entrepreneurs and farmers). But smart delivery and implementation can lead to positive impacts. Addressing constraints often requires incentives and nudges but what is also needed is to take on women’s subordinate position in the family and the traditional division of labor for household chores and care in many contexts. Finally, it must be emphasized that the estimates of the losses from gender inequality provided in this note relate only to lifetime labor earnings and human capital wealth for women. Many other economic benefits would arise from gender equality apart from those estimated in this note. The good news is that achieving greater gender equality in labor markets and other areas will generate substantial economic gains for countries apart from a better life for women. 19 | THE COST OF GENDER INEQUALITY: UNREALIZED POTENTIAL: THE HIGH COST OF GENDER INEQUALITY IN EARNINGS | MAY 2018 MAY 2018 | THE COST OF GENDER INEQUALITY: UNREALIZED POTENTIAL: THE HIGH COST OF GENDER INEQUALITY IN EARNINGS | 20 APPENDIX 1: CONCEPTUAL higher earnings for women), gender equality will reduce poverty. Since girls and women from lower socio-economic FRAMEWORK FOR backgrounds are the most affected by gender inequality, promoting gender equality will also contribute to shared ESTIMATING IMPACTS prosperity. AND COSTS Apart from providing estimates of the impacts of gender inequality on various development outcomes and the costs This series of notes aims to measure the economic cost of associated with these impacts, the notes in this series gender inequality globally and regionally by looking at the will also review the available evidence on what works to impacts of gender inequality and the associated costs in promote gender equality in various domains, as done in this multiple domains. The series also aims to provide a synthesis note for policies related to employment opportunities for of the available evidence on successful programs and policies women. Building on this series of notes, a comprehensive that have been shown to contribute to gender equality in report will be prepared to summarize the main findings as multiple areas. they pertain to the various domains of impacts, costs, and policy interventions. The framework for the analysis of impacts and costs builds on recent work on the economic impacts of child marriage, low educational attainment for girls, and human capital wealth at the World Bank. Conceptually, the series will focus on five potential domains of impacts of gender inequality, as shown in Figure A1: (1) fertility and population growth; (2) health and nutrition; (3) child marriage and educational attainment; (4) labor force participation and earnings; and (5) agency, including decision-making and the risk of gender-based violence. The impacts of gender inequality in these areas will be estimated. This note focuses on labor force participation and earnings using human capital wealth data for the estimation. Future notes in the series will look at other domains of impacts. Once impacts in various domains are estimated, costs can be measured. As shown in Figure 1, the notes will provide estimates of the monetary benefits from ending gender inequality among others in terms of (i) Higher growth in GDP per capita and lesser budgetary needs for service provision as a result of lower population growth; (ii) Higher labor earnings as a result of better health and less stunting in childhood; (iii) Higher labor earnings for women in adulthood (the focus of this note); and (iv) Benefits associated with children’s lives saved. This list of benefits is by no means exhaustive, but it includes some of the largest benefits that can be expected. Finally, as also suggested in Figure 1, the benefits from gender equality at the levels of individuals and households have broader implications at the national and even global levels. By raising standards of living (among others through higher GDP per capita with lower population growth and 21 | THE COST OF GENDER INEQUALITY: UNREALIZED POTENTIAL: THE HIGH COST OF GENDER INEQUALITY IN EARNINGS | MAY 2018 FIGURE A1: CONCEPTUAL FRAMEWORK FOR MEASURING THE COST OF GENDER INEQUALITY Associated Losses/Gains Development 5 Domains of “Impacts” Outcomes Welfare Fertility and population growth Gains GENDER INEQUALITY World Bank twin goals: Health, nutrition and violence Reduction in Earning extreme poverty Gains and shared Educational attainment Complex direct and prosperity (growth and child marriage indirect “impacts” for the bottom 40 percent) Budget Labor, Earnings & Productivity Savings Decision-making and violence Other Benefits Source: Adapted from Wodon (2017). APPENDIX 2: surveys. Estimates of expected earnings are based on Mincerian wage regressions. The regressions are used to METHODOLOGY FOR compute expected earnings throughout individuals’ working life, considering their sex, education level, and assumed HUMAN CAPITAL WEALTH experience (computed based on age and the number of years of education completed). Expected earnings are computed ESTIMATES for all individuals in the surveys from age 15 to age 65, noting that some individuals may go to school beyond age 15. The Human capital wealth is defined as the discounted value of analysis also considers the life expectancy of the labor force. future earnings for a country’s labor force. In practice, we In countries with high life expectancy, workers are expected estimate how likely it is that various types of individuals will to work until age 65, but in other countries they may not be be working, and how much they will earn when working. able to. For simplicity, when estimating the present value of By “various types” of individuals, we mean individuals future earnings, the same discount factor for future earnings categorized by age, sex, and level of education. Essentially, is applied to all countries. we use household surveys to construct a dataset that captures (1) the probability that individuals are working The household surveys used for the computation of the depending on their age, sex, and years of education; and earnings profiles—as well as the probability of working—are (2) their likely earnings when working, again, by age, sex nationally representative. The surveys are in most cases and years of schooling. This is done separately for men and of good quality, but they may still generate estimates women, and results in estimates of human capital wealth by that are not consistent with either the system of national gender. Typically, women earn significantly less than men. accounts or population data for the countries. Therefore, two adjustments are made. First, to ensure consistency Estimates of the likelihood of working for individuals are of the earnings profiles from the surveys with published based on observed values in household and labor force data from national accounts, earnings estimates from the MAY 2018 | THE COST OF GENDER INEQUALITY: UNREALIZED POTENTIAL: THE HIGH COST OF GENDER INEQUALITY IN EARNINGS | 22 surveys are adjusted to reflect the share of labor earnings school), whether individuals work (labor force participation), (including both the employed and the self-employed) in and for how many years they work (accounting for health GDP as available in the Penn World Tables. Second and conditions through life expectancy). Estimations of human separately, the estimations also rely on two variables obtained capital wealth are done separately for men and women. from data compiled by the United Nations Population This means that once we have estimates of human capital Division: (1) population data by age and sex (so that the wealth by gender, we can estimate losses in human capital data in the household surveys can be better calibrated); wealth due to gender inequality in a very simple way. If we and (2) mortality rates by age and gender (so that the denote a country’s human capital wealth as measured from expected years of work can be adjusted, accounting for the the expected future earnings of women and men as HCM fact that some workers will die before age 65). Again, we and HCW, respectively, and the adult population of men and adjust data from the surveys to population estimates from women by POPM and POPW, the earnings per adult men and the United Nations to ensure that estimates are adequate. women can be defined as hcM=HCM/POPM and hcW=HCW/ For individuals in the 15-to-24 age group, the probability of POPW. Under gender equality, interpreted as ensuring remaining in school is also considered. that adult men and women have the same future expected earnings, human capital for women would increase from hcW Given the estimation of human capital wealth based on to hcM. Therefore, the loss in human capital wealth from Mincerian wage regressions, the measure accounts not gender inequality is measured as (hcM-hcW)×POPW. 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Geneva: The World Economic Forum. 25 | THE COST OF GENDER INEQUALITY: UNREALIZED POTENTIAL: THE HIGH COST OF GENDER INEQUALITY IN EARNINGS | MAY 2018 Recommended citation for this note: Wodon, Q., and B. de la Brière. 2018, Unrealized Potential: The High Cost of Gender Inequality in Earnings. The Cost of Gender Inequality Notes Series. Washington, DC: The World Bank. This note was prepared by a team at the World Bank. The team acknowledges support for this note as part of a work program funded by the Canadian Government, the Children’s Investment Fund Foundation, and the Global Partnership for Education. This work builds on a previous study at the World Bank on the Changing Wealth of Nations, with special thanks to Glenn-Marie Lange. The authors are grateful among others to Sameera Al Tuwaijri, Niklas Buehren, and Oni Lusk-Stover for valuable comments. Luis Benveniste and Caren Grown provided both comments and strategic guidance. The authors are also grateful to Stefano Mocci and Meskerem Mulatu for their support, and Chris Walsh and Patricia da Camara for communications and dissemination. The findings, interpretations, and conclusions expressed in this note are entirely those of the authors and should not be attributed in any manner to the World Bank, its affiliated organizations or members of its Board of Executive Directors or the countries they represent. Citation and the use of material presented in this note should take into account its provisional character. The World Bank does not guarantee the accuracy of the data included in this work. Information contained in this note may be freely reproduced, published or otherwise used for noncommercial purposes without permission from the World Bank. However, the World Bank requests that the original study be cited as the source. © 2018 The World Bank, Washington, DC 20433. MAY 2018 | THE COST OF GENDER INEQUALITY: UNREALIZED POTENTIAL: THE HIGH COST OF GENDER INEQUALITY IN EARNINGS | 26 THE COST OF GENDER INEQUALITY: UNREALIZED POTENTIAL: THE HIGH COST OF GENDER INEQUALITY IN EARNINGS